Short-term exposures to higher temperature and heat waves have been associated with adverse acute cardiovascular and respiratory mortality, but less is known about the chronic effects of weather. We propose to evaluate the chronic adverse health risks associated with long-term exposure to fluctuations in the weather parameters in persons aged over 64 years on a national scale, focusing on mortality in all Medicare enrollees, and in subjects with specific cardiovascular and neurological conditions. We will identify how the health risks changed over the years, and use this information to make predictions of how the risks will change under different climate scenarios. In a recent paper we showed that long-term exposure to high day-to-day variability in summer temperatures (defined as the standard deviation of daily levels of summer temperature) might elevate the risk of mortality in different subgroups of susceptible populations of elderly1. In this project we will partner with the Atmospheric Chemistry Modeling Group at Harvard: (1) to estimate the chronic effects associated with long-term exposure to higher day-to-day variability in temperature and in water vapor pressure (WVP) within summer months (June-August) on mortality in all Medicare enrollees; (2) to examine the chronic effects on mortality in subject with specific conditions such as cardiovascular and neurological disease; (3) to identify characteristics of city (e.g. socio-economic status, percent of green space climate zone, population in poverty, percent of population by race, air conditioning prevalence) which modify the risk of dying. Specifically, we will identify whether changes in weather related risk over time and space are associated to changes in urban structure, air conditioning prevalence, and socioeconomic status both within city and across cities, and whether differences in sensitivity to weather variability across locations are related to green space and population characteristics. Importantly, these city level characteristics will be defined on the zip-code level, not the city level, allowing us to capture te impact of true local land use. (4) Finally, we will predict how life expectancy will change with increasing variability of summertime temperatures in a future atmosphere. An innovative aspect of our investigation is that we will focus on less explored weather parameters such as variability in temperature and variability in WVP. We will analyze the data using novel statistical methods (survival models with time-varying factors and meta-regression models). The findings of this national analysis will advance statistical analyses of climate change data and knowledge of the impacts of temperature and humidity variability on life expectancy. By producing results that can be extrapolated to the future, by identifying the covariates that explain the differences in temperature related mortality over time and across cities, we will identify key factors important for adaptation and mitigation strategies. Results of our study will aid NIH by identifying specific cardiovascular disease that might exacerbate risk, which will lead to targeted and cost effective interventions.